We are using global genomic approaches to profile clinical specimens that are associated with different stages of liver diseases. For example, we have identified a unique diagnostic signature for patients with early onset of liver cancer. We have also developed and validated a unique molecular signature based on the mRNA gene expression of metastatic primary hepatocellular carcinoma (HCC) specimens to predict prognosis and metastasis of HCC patients. Importantly, we found that this molecular signature could identify those patients who were most at risk for recurrence even in patients with early stage disease. More recently, we have integrated genomic and transcriptomic profiles to search for metastasis driver genes. We found that primary tumor lesions and their match distant metastasis were largely similar, however significant differences could be identified between primary tumors with or without accompanying metastasis. Moreover, metastasis genes were principally tumor type and organ-site-specific. These findings further solidify that metastatic propensity is inherent to the primary tumor. We have also developed a unique molecular prognostic signature based on mRNA gene expression of the liver microenvironment of HCC patients. We found that a predominant humoral cytokine profile occurs in the metastatic liver microenvironment and that a shift toward anti-inflammatory/immune-suppressive responses may promote HCC metastases. Interestingly, the tumor signature is principally different from that of liver microenvironment. We have recently further explored the contribution of the liver microenvironment to HCC initiation and progression by asking whether activated hepatic stellate cells (A-HSCs), stromal cells which participate in repair following injury and in the development of fibrosis, contribute directly to HCC recurrence. We identified and validated an A-HSC-specific gene expression signature among nontumor tissues of HCC patients that was associated with HCC recurrence and survival. Further studies showed that A-HSCs preferentially alter monocyte populations to induce protumorigenic and progressive features by shifting their gene expression from an inflammatory to an immune suppressive signature. These findings indicate that disruption of the interactions and signaling events between inflammatory cells and components of the microenvironment may be useful therapeutic strategies for preventing HCC relapse. In addition, we have used molecular profiling to identify five genes that may serve as biomarkers for early onset of HCC, especially for those that are negative for alpha-fetoprotein. We have also explored the role of small non-coding RNAs, termed microRNAs, in HCC metastasis and survival. We found that certain microRNAs are associated with metastasis and could significantly predict patient survival and relapse even in early stage disease, while cCertain microRNAs (e.g. microRNA-26) are gender-related. Patients with low microRNA-26 expression had poor survival and were better responders to interferon therapy than those with normal expression. We have since developed a qRT-PCR-based matrix template and scoring algorithm (MIR26-DX) to assign patients into either low or high microRNA-26 groups. Patients with low microRNA-26 levels selected by the template were those that responded favorably to interferon-alpha therapy. We have now initiated a multi-center randomized control clinical trial in China based on these findings (NCT01681446). We have also recently used integrative approaches to identify HCC driver genes. For example, we have combined high-resolution, array-based comparative genomic hybridization and transcriptome analysis of HCC samples to identify and validate a 10-gene signature associated with chromosome 8p loss and poor outcome. Functional studies demonstrated that three gene products among the 10-gene signature have tumor suppressive properties. Recently we have shown that two of the chromosome 8p tumor suppressor genes, SORBS3 and SH2D4A, are physically and functionally linked and provide a molecular mechanism of inhibiting STAT3-mediated IL-6 signaling in HCC cells. We have also integrated metabolite and mRNA profiles to define key signaling events that can alter the fitness of EpCAM+ AFP+ HCC cancer stem cells. Our analysis revealed tumor-specific and stem-cell-like-specific metabolites linked to patient survival along with correlating significant genes in the stem cell-like tumor subgroup. In particular, stearoyl CoA desaturase (SCD), a key enzyme involved in fatty acid biosynthesis, and its related metabolites were highly elevated in stem cell-like HCC and are associated with HCC survival and may functionally contribute to HCC stemness and aggressiveness. We have also compared and contrasted global metabolic profiles between liver, breast and pancreatic cancer tissues and found that metabolites are principally unique to each tissue and cancer type. Thus, metabolic profiling could be applied as cancer classification tools to differentiate tumors based on tissue of origin. To aid in the integration of multiple omics data, we have proposed an integrative subgraph mining approach, called iSubgraph to discover patterns of miRNA-gene networks which could be used for patient stratification in HCC. This algorithm could detect cooperative regulation of miRNAs and genes with highly stable class predictions. The HCC subgroups identified by the algorithm have different survival characteristics with key roles of specific genes in HCC subgroups. Thus, our method can integrate various omics data derived from different platforms and with different dynamic scales to better define molecular tumor subtypes. We hypothesized that alpha-fetoprotein (AFP)+ and AFP- tumors differ biologically. Using global microRNA profiling, we found that miR-29 family members were significantly down-regulated in AFP+ tumors with a significant inverse correlation between miR-29 and DNMT3A gene expression. We also show that AFP+ and AFP- HCC tumors have distinct global DNA methylation patterns, with an increased DNA methylation in AFP+ HCC. AFP expression induces protumorigenic features along with miR-29a inhibition and DNMT3A induction. AFP also inhibited transcription of the miR-29a/b-1 locus via c-MYC binding to the miR-29a/b-1transcript. Further, AFP expression promotes tumor growth of AFP- HCC cells in nude mice. Thus, tumor biology differs considerably between AFP+ HCC and AFP- HCC and that AFP is a functional antagonist of miR-29, which may contribute to global epigenetic alterations and poor prognosis in HCC. While HCC is the most frequent form of primary liver cancer (PLC) worldwide, with rising incidence in the western countries, the incidence of cholangiocarcinoma (CCA), a bile-duct-related cancer and second most frequent PLC, is prevalent, especially in the north-east area of Thailand. We have initiated the Thailand Initiative for Genomics and Expression Research in Liver Cancer (TIGER-LC) to provide a comprehensive global analysis of genomic alterations related to the primary liver cancer types in Thai liver cancer patients. The findings of this study will not only allow us to more clearly understand the biological signaling related to primary liver cancer types and subtypes, but will also allow us to identify relevant health disparity genomic biomarkers that are related to etiological risk factors or ethnic groups by comparing our results with that of other populations. Furthermore, our study may identify novel, clinically useful biomarkers or targets to improve the health and outcome of patients suffering from this deadly disease. Thus, TIGER-LC is expected to have a major global health impact on improving the outcome of patients with liver cancer.